A Linkage Approach to Managing Your Business

1
A Linkage Approach to Managing Your Business

• Kunal Gupta, Ph.D.
• Senior Consultant
• Decision Sciences
• Kunal.gupta_at_burke.com

AMA Regional Conference May 2-3, 2005
2
Tutorial Overview

• Introduction
• Linkage Research and Analysis
• Origins of linkage analysis
• Focus of linkage analysis
• Rational of linkage research and analysis
• Critical linkages
• Challenges
• Case Studies
• The Process of Linkage Analysis
• Recommended Process
• Overall Summary and Conclusion

3
Linkage Research and Analysis
4
Origins of Linkage Analysis

• A variety of management perspectives have gained
  widespread acceptance during the last 15 years
• Malcolm Baldrige Criteria for Performance
  Excellence
• European Foundation for Quality Management
• Service-Profit Chain Model
• The Balanced Scorecard
• Linkage Research Model
• Six Sigma and the Language of Xs and Ys
• Action-Profit-Linkage Model
• All of the above emphasize
• Holistic, enterprise-wide perspective
• Balanced organizational performance measurement
  and evaluation
• Linkage, integration, and alignment

5
The Action-Profit-Linkage Model
Source Epstein, M. J. Westbrook, R. A.
Linking Actions to Profits in Strategic
Decision Making. MIT Sloan
Management Review, Spring, 2001 39-49.
6
Burkes Framework for Enterprise Value
Management (EVM)
Key organizational decision areas supported by
Burke are Leadership, People Management,
Product/Service Management and Process Management.
Leadership
People Management
Product/Service Management
Process Management
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Kaplan and Nortons Perspective
The complexity of managing an organization today
requires that managers be able to view
performance in several areas simultaneouslyno
single measure can provide a clear performance
target, or focus attention on all critical areas
of a business.
The Balanced Scorecard Harvard Business Review
8
Focus of Linkage Analysis
Linkage research and analysis is rapidly-growing
as an area of importance to all organizations.
Linkage research and analysis is aimed at
establishing

• How key business results are related to effective
  management of customer experiences and
  relationships
• How effective management of customer experiences
  and relationships, in turn, is linked to and
  driven by effective alignment of people and
  processes within an organization.

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Linking Business Results to Customer Experiences
Computer Supplies
88
90
80
57
70
Percentage of Retained Customers
60
50
30
25
40
30
20
10
0
Vulnerable
Dissatisfied
Secure
Satisfied
10
Linking Business Results to Customer Experiences
Telecommunications
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Linking Business Results to Customer Experiences
Industrial Products

• Customer Percent of Percent of Customers
• Segment Classification Customer Base Where Share
  of Business
• Increased Decreased
• Secure/Loyal 55 61 2
• Still Favorable 26 44 8
• Moderate Risk 18 22 22
• Dissatisfied 1 0 100

?
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Linking Customer Experiences to Alignment of
Processes - Support
Relationship Between Customer Satisfaction and
Process Cycle Time
Higher
Dis
/satisfaction
Threshold
Customer Satisfaction with Total Time To
Resolve Problem
Lower
0
2
4
6
8
10
12
14
16
18
20
22
24
28
Number of Hours to Close Trouble Call
13
Linking Customer Experiences to Alignment of
People - Banking
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Rationale for LinkageResearch and Analysis

• There are at least two trends that are driving
  the recent interest in and growth of linkage
  research and analysis
• Desire for improved managerial confidence in and
  support for decisions regarding where/how to
  invest organizational resources
• Growing need to understand and align performance
  management within and beyond organizational
  boundaries

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Critical Linkages

• Leading and lagging indicators, and/or multiple
  data sources reflecting a single enterprise
  dimension or voice, such as
• Transactional and Relationship Customer and
  Market Surveys
• Survey and Non-Survey Customer or Market Data
• Linkages across multiple enterprise dimensions
  and data sources, such as
• Customer Loyalty ? Financial/Market Results
• Employee Engagement ? Customer Loyalty
• Process Cycle Time ? Customer Satisfaction

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The Challenge of Linkage

• The ideal situation for analyzing and integrating
  data from multiple streams would involve common
  data points for which all relevant measures are
  available.
• Unfortunately, the ideal situation almost never
  exists, especially at a single point-in-time.
• As a result, linkage typically is a matter of
  approximating the business model by piecing
  things together.

17
Case Studies
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The Intent

• Linkage analysis is purported to provide a
  variety of benefits, including but not limited
  to
• Decision support with strategic decision making
• Proof of concept
• Revitalizing existing measurement programs
• Correcting measurement myopia
• In this section of the session, we will share
  some selected case studies that have each
  addressed one or more of the objectives listed
  above.

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Strategic Decision Making
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Impacts of Cost Reduction

• A leading retail bank was undertaking a cost
  reduction exercise that entailed reducing the
  number of tellers in each branch.
• However, reduction in the number of tellers would
  have generated two counter forces
• Increased profits because of cost reductions
• Likely reduction in profits because of the
  detrimental impact on customer experience and
  therefore loyalty
• More wait time in branches ? Reduced favorability
  of customer experience ? Reduced overall customer
  loyalty ? Reduced customer buying activity of
  various bank offerings
• Burke was therefore asked to examine the
  empirical evidence, through linkage analysis, for
  estimating the second of the two objectives
  i.e. reduction in profits because of lower
  customer loyalty
• We analyzed three types of data
• In branch customer experience (survey) data
• Overall customer loyalty / relationship (survey)
  data
• Actual customer behavior data

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Impacts of Cost Reduction (continued)

• We then used the results of the linkage analysis,
  to provide an estimate of the reduction in branch
  level sales for every 1000 bank branch customers.
• While we show the summary of (disguised) results
  below, the linkage model went through more
  detailed analysis to clearly identify
• The impact of increased waiting time on the
  customers overall branch experience
• The impact of a less favorable branch experience
  of overall customer loyalty towards the bank
• The estimated reduction in current and future
  business that customers would give to the bank
  because of reduced overall loyalty
• The impact of such behavior of branch level
  profits
• The bank then used such information, along-with
  their internal information on cost savings
  associated with the planned reduction of tellers,
  to help them with the strategic discussion
  underway.

22
Resource Investment Priorities

• A retail institution asked us to aid their
  resource investment decision process by analyzing
  data from their associate (i.e. employee),
  customer, demographic, and financial measurement
  at the store level.
• We examined data across these different data
  streams in one comprehensive model to estimate
• The direction of causality do more engaged
  associates create loyal customers, or does
  customer loyalty foster associate engagement
• The time lag of causality is there a lag
  between customer loyalty and customer behavior,
  and if yes what is the period of lag
• Everything else being equal do the
  characteristics of the store neighborhood have a
  significant impact on a stores financial
  performance
• Identification of the store departments with
  maximal impact on customer loyalty
• Estimated financial impact of each associate as
  well as customer survey measure on the
  profitability of individual stores

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Resource Investment Priorities (contd.)

• The results provided information that helped the
  firm take some strategic resource investment
  issues pertaining to
• Areas of investment that could foster associate
  engagement and/or customer loyalty, and therefore
  the profitability of individual stores
• An understanding of the immediacy of customer
  loyalty on the financial performance of the store
• Identification of demographic properties of the
  store neighborhood (e.g. median HH income) with a
  strong impact on the financial performance of the
  store

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Proof of Concept
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Show me the Money!
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The Eureka Moment

• They worked with me to define the project and
  helped us when different turns were needed. They
  hung in there and together we achieved our goal.
  We were successful in our goal of doing financial
  linkage . Technology Firm, Audit Date 2002
• Often times, the customer loyalty programs need
  to be rejuvenated to help their custodians earn
  a seat at the table.
• Demonstrating the linkages between customer
  attitudes and customer behavior can provide the
  much needed impetus to customer loyalty programs
• In the recently concluded IIR conference (Feb.,
  2005) organizations across industries were
  looking for such proof to present to senior
  management.
• Overall, while it is very important to provide
  such proof of concept, there is no reason that
  such evidence cannot be extended closer to more
  operational linkage models.

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Working the Momentum
L5 VOW
L4 Operational Metrics
L3 Transactional Surveys
L2 Product Specific Surveys
L0 Financial Results
L1 Relationship Surveys
Phase 1
Phase 2
Phase 4
Phase 3
Phase 5
Phase 6
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Revitalizing Existing Measurement Programs
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Missing Critical Information

• Very early on in one of the linkage projects,
  through the blueprinting and linkage assessment
  phase, we identified the inability of current
  measurement programs to provide quality decision
  support to the senior management of the firm.
• The financial success of this firm is strongly
  contingent on the willingness of sales
  individuals in various retail outlets to
  recommend the products of the firm.
• However, despite the critical importance of such
  sales individuals for financial success, the firm
  recognized the lack of any systematic measurement
  data on its channel partners.
• Absence of such data provided the firm with
  little, if any, information on creating more
  engaged channel partners.
• Such recognition resulted in major re-allocation
  of measurement resources to provide funding for a
  channel partner study.

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Correcting Measurement Myopia
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The Concept of Measurement Myopia

• Often times, firms have a multitude of measures
  (survey as well as non-survey) that all purport
  to aid the decision making ability of the firm.
• More often than not however, these well
  established measures and metrics do not provide
  the level of seamless and integrated decision
  support they are designed to offer.
• For instance, if the chosen metric of customer
  affinity does not link to favorable customer
  behavior, then increased customer affinity scores
  will not lead to improved financial performance
  of the firm.
• In this section, we discuss one case study that
  demonstrates the ability of linkage analysis to
  overcome such measurement myopia.

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Revisiting the Employee Engagement Index

• A large financial institution has had an
  Employee Engagement Index (EEI) measure in
  place for years.
• Individual managers as well as divisions take the
  index score very seriously because of the mandate
  from senior management.
• Senior management believed that superior employee
  engagement scores, as defined, should lead to
  three key benefits
• Superior customer experience
• Reduced employee turnover
• Improved employee productivity
• In a recently concluded linkage assignment
  however, we observed that the existing EEI was
  sub-optimal in providing the first two of these
  three benefits.
• This initiated the development and establishment
  of a new EEI-Revised that comprised of measures
  with stronger ability to link to
• Favorable customer experience perceptions
• Reduced employee turnover levels

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The Process of Linkage Analysis
34
Recommended Process

• Create linkage and integration steering team
• Develop the linkage blueprint
• Conduct inventory of existing data and assess
  feasibility of linkage analysis
• Identify and prioritize links to be investigated
• Locate and assemble relevant data required to
  perform analyses
• Analyze data to establish linkages and test
  hypothesized relationships
• Refine and deploy the linkage results in
  marketing planning and action
• Use learning as a basis for ROI simulations and
  other what if scenario evaluations
• Align key variables and optimize performance
  targets for upstream metrics

35
Recommended Process

• Create linkage and integration steering team
• Develop the linkage blueprint
• Conduct inventory of existing data and assess
  feasibility of linkage analysis
• Identify and prioritize links to be investigated
• Locate and assemble relevant data required to
  perform analyses
• Analyze data to establish linkages and test
  hypothesized relationships
• Refine and deploy the linkage results in
  marketing planning and action
• Use learning as a basis for ROI simulations and
  other what if scenario evaluations
• Align key variables and optimize performance
  targets for upstream metrics

36
Create the Steering Team

• To ensure the process is collaborative and to
  avoid the not invented here syndrome, a
  cross-functional group is required
• The blueprinting team generally is comprised of
  representatives from
• Sales
• Marketing
• Finance
• Production/Operations
• Business or Strategic Planning
• Human Resources
• Management Information/IT
• Both managers and stewards of relevant data in
  each of the above areas are potential candidates
  for the steering team.

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Recommended Process

• Create linkage and integration steering team
• Develop the linkage blueprint
• Conduct inventory of existing data and assess
  feasibility of linkage analysis
• Identify and prioritize links to be investigated
• Locate and assemble relevant data required to
  perform analyses
• Analyze data to establish linkages and test
  hypothesized relationships
• Refine and deploy the linkage results in
  marketing planning and action
• Use learning as a basis for ROI simulations and
  other what if scenario evaluations
• Align key variables and optimize performance
  targets for upstream metrics

38
Rationale for Blueprinting

• Most managers and executives have a mental
  picture of the road to business results, but
  this image and tacit knowledge often is not
  documented and shared throughout the
  organization.
• A linkage blueprint furnishes a detailed
  illustration of the hypothesized relationships
  among key operational, product, employee, and
  customer elements which, if they are managed
  effectively, lead to desired financial and other
  business results.
• Development of a blueprint is a critical first
  step towards successful linkage analysis and
  modeling. In fact, failure to develop such a
  blueprint is one of the main reasons that many
  organizations are ineffective in their linkage
  analysis and modeling efforts.

39
Balanced Performance Measurementin Most
Companies Today A Reality Check

• Many companies believe they have solved the
  problem of balanced performance measurement by
  adopting a framework like the Balanced Scorecard,
  mistaking it for an off-the-shelf checklist
  procedure that is universally applicable and
  completely comprehensive. But using such a
  framework by itself wont help identify which
  performance areas and which drivers make the
  greatest contribution to a companys financial
  outcomes More successful companies have attacked
  the problem by choosing their performance
  measures on the basis of causal models, also
  called value driver maps, which layout the
  plausible cause-and-effect relationships that may
  exist between the chosen drivers of strategic
  success and outcomes.

Christopher Ittner and David Larcker Coming Up
Short on Nonfinancial Performance
Measurement Harvard Business Review (November,
2003)
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What is a Blueprint Session

• Interactive discussion with key business leaders
  to build the business model for each specific
  business.
• The output is a business model that positions
  customer perceptions and behaviors as a central
  component between desired downstream financial
  results and upstream operations measures.

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Why Conduct a Blueprint
Current mean income contribution to the
organization 611
Share of Wallet
725
391
Base
550
Low vs. Medium Significant at 95 Low vs. High
Significant at 99 Medium vs. High Supported
directionally
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Questions to Build the Blueprint

• Focus on customer-centricity to answer four key
  questions
• How is income generated from buyers or customers?
• What are the drivers and determinants of customer
  preference or loyalty?
• What are operational enablers or means of
  addressing the key drivers of customer preference
  or loyalty?
• What are employee enablers or means of addressing
  the key drivers of customer preference or
  loyalty?

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A Case Illustration
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Example of a Blueprint for Retail Banking
How is income generated from buyers or customers?
Commissions
Share of Financial Services Wallet

Income
Interest
Account Activity
Customer Preference or Loyalty
Number Type of Accounts
Fees
Profitability
Costs
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Example of a Blueprint for Retail Banking
What are the drivers and determinants of customer
preference or loyalty?
Institutional Stability
Reputation
Products Services
.
Corporate Citizenship
Barriers to Switching
Perceptions of the Brand
Marketing Communications
.
Value Received
Customer Preference or Loyalty
Accessibility
.
Perceptions of Service Experiences
Quality of Facilities Channels
Evaluation of Alternatives
Interactions with Staff
Response to Requests or Problems
Account Performance or Usage
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Example of a Blueprint for Retail Banking
What are employee enablers or means of addressing
the key drivers of customer preference or loyalty?
Barriers to Switching
Perceptions of the Brand
Service Orientation
.
Value Received
Customer Preference or Loyalty
.
Perceptions of Service Experiences
Employee Retention
Productivity Efficiency
Employee Satisfaction Commitment
Evaluation of Alternatives
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Example of a Blueprint for Retail Banking
What are operational enablers or means of
addressing the key drivers of customer preference
or loyalty?
Barriers to Switching
Perceptions of the Brand
Channel Accessibility
.
Value Received
Customer Preference or Loyalty
Channel Availability
.
Perceptions of Service Experiences
Easy to Use Channels
Evaluation of Alternatives
Customer Information Systems
Service Cycle Time
Appearance of Facilities
48
Bringing the Pieces Together
Financial
Customers
Employees
Processes Operations
49
Recommended Process

• Create linkage and integration steering team
• Develop the linkage blueprint
• Conduct inventory of existing data and assess
  feasibility of linkage analysis
• Identify and prioritize links to be investigated
• Locate and assemble relevant data required to
  perform analyses
• Analyze data to establish linkages and test
  hypothesized relationships
• Refine and deploy the linkage results in
  marketing planning and action
• Use learning as a basis for ROI simulations and
  other what if scenario evaluations
• Align key variables and optimize performance
  targets for upstream metrics

50
The Data Inventory

• For each element of the blueprint, an attempt to
  identify a relevant measure or data source must
  be undertaken
• The process of data inventory reveals several key
  insights
• It identifies existing data that may be analyzed
  to breathe life into the blueprint.
• It enables the linkage researcher to determine if
  the data are organized in a manner that provides
  appropriate units of analysis.
• It reveals any gaps between the blueprint and
  currently available data that need to be filled.

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Data Inventory Template
Data Source Location
Data Owner or Steward
Units of Organization
History or Longevity
Identifier
Financial Business Results
Customer Market
Employee Stakeholders
Process or Operations
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Recommended Process

• Create linkage and integration steering team
• Develop the linkage blueprint
• Conduct inventory of existing data and assess
  feasibility of linkage analysis
• Identify and prioritize links to be investigated
• Locate and assemble relevant data required to
  perform analyses
• Analyze data to establish linkages and test
  hypothesized relationships
• Refine and deploy the linkage results in
  marketing planning and action
• Use learning as a basis for ROI simulations and
  other what if scenario evaluations
• Align key variables and optimize performance
  targets for upstream metrics

53
Identify and Prioritize Links to be Investigated

• Obviously, only elements of the blueprint for
  which appropriate data are available may be
  investigated.
• Prioritization of the links that are capable of
  being investigated should take into account
• Impact in terms of furnishing proof of concept
• Strategic importance
• Alignment with current or near-term initiatives
• Think outside-in
• Quite often, building the business case for
  customer centricity is the most effective way to
  secure organizational and managerial engagement
  in the remainder of the linkage effort

54
Recommended Process

• Create linkage and integration steering team
• Develop the linkage blueprint
• Conduct inventory of existing data and assess
  feasibility of linkage analysis
• Identify and prioritize links to be investigated
• Locate and assemble relevant data required to
  perform analyses
• Analyze data to establish linkages and test
  hypothesized relationships
• Refine and deploy the linkage results in
  marketing planning and action
• Use learning as a basis for ROI simulations and
  other what if scenario evaluations
• Align key variables and optimize performance
  targets for upstream metrics

55
Locate and Assemble the Data

• This is almost never as easy as initially
  expected because of
• Data structure
• So-called legacy systems
• Data ownership and stewardship
• Availability of compatible identifiers or
  match-and-merge hooks
• Data assembly and preparation is likely to take
  more time than originally planned.
• Additional considerations include
• Privacy and confidentiality
• Data security procedures
• Legal and regulatory issues

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Overall Summary and Conclusion
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In Conclusion

• Linkage research and analysis can be used to
  inject energy and momentum into existing
  measurement programs.
• Providing management with the confidence that
  customer loyalty links to the financial success
  of the firm can help market research managers
  earn a seat at the table.
• Linkage analysis also allows a firm to review
  each measurement data point with greater
  intelligence to ensure that it leads to the
  desired marketplace and financial success, e.g.
• Does the employee engagement index lead to
  superior customer experience
• Does the process measure lead to superior
  customer experience
• Does customer loyalty lead to improved results
• While linkage analysis is exciting, the
  associated process is complex and challenging.
• The ability to follow a robust process however
  ensures the success of not only linkage research
  and analysis, but also of linking various
  measurement programs into one comprehensive
  decision support framework.
• In case study after case study, we have observed
  that once successful, such efforts provide
  extreme value to all the investments made in
  various organizational programs.